Background

Chinese jujube (Ziziphus jujuba Mill.) is a popular fruit crop species that is native to China and is highly desired by consumers worldwide due to the abundant nutritional and health benefits of the fruit [1, 2]. However, the flesh jujube fruit has a very short shelf-life underlined by rapid dehydration or water-soaking deterioration within 2–3 days after harvest [3]. Therefore, fruit storage and quality maintenance have been among the most urgent challenges in the development of the jujube industry, whereas knowledge related to its ripening characterization and regulation is lacking. Over the past few decades, great strides have been made in elucidating the regulation of fruit ripening [4]; in particular, ethylene and abscisic acid (ABA) are recognized as the most important phytohormones that are directly or indirectly involved in the ripening of both climacteric and non-climacteric fruit [5, 6]. Recently, Chinese jujube has been characterized as a non-climacteric fruit, while a basal level of ethylene is still needed to maintain full fruit maturity [7]. These findings also reveal that the regulation of ripening is relatively complex and that there is a further need to explore these mechanisms to deepen our understanding of the ripening of Chinese jujube fruit.

With regard to ABA, the presence of dramatically increased levels in fruit during the onset of ripening has been reported in several fruit crop species, including grape [8], sweet cherry [9], cucumber [10], watermelon [11], and persimmon [5], which points to a role for ABA in triggering the onset of fruit ripening [8]. Moreover, applications of exogenous ABA and nordihydroguaiaretic acid (NDGA, an inhibitor of ABA biosynthesis) have enabled us to identify ABA-dependent pathways [12, 13]; increased numbers of research findings have suggested a positive role for ABA in promoting the metabolism and accumulation of soluble sugars [12, 14], formation of peel color [15, 16], and modification of cell wall catabolism [17], thereby accelerating ripening processes [5]. Fruit ripening is a highly integrated process that involves hormone control and crosstalk, as well as alterations to the numbers of transcripts of transcription factors (TFs) [61]. In the starch biosynthesis pathway, genes encoding ADP-glucose pyrophosphorylase and isoamylase were downregulated by ABA, while NDGA downregulated the expression of genes controlling starch degradation, including two alpha-amylase- and a beta-amylase-encoding genes. These results suggested that ABA was involved in starch metabolism, just as ZmEREB156 positively modulated starch biosynthesis via the synergistic effect of sucrose and ABA in maize [85]. For identification of differentially expressed genes (DEGs), an edgeR program [86] in OmicShare tools, a free online platform for data analysis (http://www.omicshare.com/tools), was used with a fold change (FC) threshold ≥2 and an false discovery rate (FDR) ≤ 0.05. The use of edgeR allowed comparative analysis within two replicates, and it had been used in several previous papers [12, 87, 88]. The functional enrichment of DEGs was determined using Gene Ontology (GO) and pathway analysis tools within the OmicShare platform [89]. We also used MapMan 3.6.0RC1 software to enrich the putative functional annotation of the DEGs [90, 91].

Quantitative real-time PCR validation for transcriptome expression levels

Total RNA was extracted using a plant RNA extraction kit (TaKaRa), and 200 ng of high-quality RNA was subsequently prepared for first-strand cDNA synthesis using a PrimeScript RT reagent kit with gDNA Eraser (TaKaRa). qPCR was then performed using a SYBR Premix Ex Taq II kit (TaKaRa) with a total volume of 10 μL, which comprised 1.0 μL of cDNA, 5.0 μL of SYBR premix solution, 0.4 μL of forward/reverse primers and 3.2 μL of dH2O. The thermal program for qPCR in a Roche LightCycler 96 system was set using the following conditions: 95 °C for 30 s; 40 cycles of amplification of 5 s at 95 °C, 30 s at 58 °C, and 30 s at 72 °C; and a default dissociation stage. The relative expression of each gene was normalized to that of a reference gene, ZjUBQ (Zhang et al. 2015), and was ultimately calculated using the 2-△Ct method (Livak and Schmittgen 2001). Sequences of the primers used for qPCR are listed in Additional file 10.

Statistical analysis

Statistical analysis was performed using the Duncan multiple range test (MRT) at the p < 0.05 level in SPSS 19.0. The error bars in the figures represent the standard deviations of three biological replicates.